Urban sprawl has led to various economic, social, and environmental problems. Therefore, it is very significant to improve the efficiency of resource usage and promote the development of compact urban form. It is a common topic that measuring urban compactness is done with certain ways and methods as well. Presently, most urban compactness measurement methods are based on two-dimensional (2D) formats, but methods based on three-dimensional (3D) formats that can precisely describe the actual urban spatial conditions are still lacking. To measure the compactness of the 3D urban spatial form accurately, a 3D Compactness Index (VCI) was established based on the Law of Gravitation and the quantitative measurement model. In this model, larger 3D Compactness Index values indicate a more 3D-compact city. However, different urban scales may influence the discrepancy scale of different cities. Thus, the 3D Compactness Index model was normalized as the Normalized 3D Compactness Index (NVCI) to eliminate such discrepancies. In the Normalized 3D Compactness Index model, a sphere with the same volume of real urban buildings in the city was assumed as the most compact 3D urban form, and which was also calculated by 3D Compactness Index processing. The compactness value of the normalized 3D urban form is obtained by comparing the 3D Compactness Index with the most compact 3D urban form. In this study, 1149 typical communities in Xiamen, China, were selected as the experimental fields to verify the index. Some of communities have a quite different Normalized 3D Compactness Index, although they have a similar Normalized 2D Compactness Index (NCI), respectively. Moreover, comparing with the 2D Compactness Index (CI) and Normalized 2D Compactness Index (NCI), the 3D Compactness Index and Normalized 3D Compactness Index can describe and explain reality more precisely. The constructed 3D urban compactness model is expected to contribute to scientific study on urban compactness.
Continuous growth of building energy consumption CO2 emission (BECCE) threatens urban sustainable development. Urban form is an important factor affecting BECCE. Compactness is a significant urban morphological characteristic. There is currently a lack of research on the effect of urban three-dimensional (3D) compactness on BECCE. To clarify the research value of 3D compactness, we investigated whether 3D compactness has a stronger impact on BECCE than two-dimensional (2D) compactness. A total of 288 buildings of the People’s Bank of China (PBOC) were divided into 5 zones according to building climate demarcation. As BECCE is affected mainly by four aspects (socioeconomic condition, building features, macroclimate, and urban form), the BECCE driven by urban form (BECCE-f) in each zone was calculated firstly using the partial least square regression model. Normalized compactness index (NCI) and normalized vertical compactness index (NVCI) were calculated with Python to quantify urban 2D and 3D compactness within a 1 km buffer of PBOC buildings. The mean NCI and NVCI values of each zone were adopted as 2D and 3D compactness of this zone. Gray correlation analysis of the five zones showed that the connection between the NVCI and BECCE-f is stronger than that between NCI and BECCE-f. Based on this, we believe that the emphasis of later research should be shifted to urban 3D form, not just 2D elements. 3D form can describe the real urban form in a more accurate and detailed manner. Emphasizing 3D morphological characteristics in studies of the relationship between urban form and building energy performance is more meaningful and valuable than only considering 2D characteristics. The impact mechanism of urban form on BECCE-f should also be analyzed from the perspective of 3D form. This study also provides beneficial solutions to building energy saving and low-carbon building construction.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.